26 to 50 of 446 scikit-learn Jobs

and Agile methodologies.Excellent analytical, problem-solving, and communication skills.Preferred SkillsExperience with data engineering, ETL workflows, or big data frameworks (Spark, Airflow).Knowledge of machine learning libraries (NumPy, Pandas, Scikit-learn, TensorFlow, etc.) is a plus.Exposure to DevOps practices, infrastructure as code, and monitoring tools (Jenkins, Terraform, Prometheus).Familiarity with security best practices for Python-based applications.Prior experience in More ❯

as a Data Scientist, ideally within customer analytics, marketing, or CRM environments. Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with More ❯

experience as a Data Scientist or in a similar role. Strong programming skills in Python, R, or SQL . Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch . Solid understanding of statistics, predictive modeling, and data mining techniques. Experience with data visualization tools such as Tableau, Power BI, or matplotlib/seaborn More ❯

Agile methodologies.Excellent analytical, problem-solving, and communication skills. Preferred Skills Experience with data engineering, ETL workflows, or big data frameworks (Spark, AirflowKnowledge of machine learning libraries (NumPy, Pandas, Scikit-learn, TensorFlow, etc is a plus.Exposure to DevOps practices, infrastructure as code, and monitoring tools (Jenkins, Terraform, PrometheusFamiliarity with security best practices for Python-based applications.Prior experience in domains More ❯

developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

as a Data Scientist, ideally within customer analytics, marketing, or CRM environments. Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with More ❯

AI Solutions Engineer AI Solutions, B2B, B2C, Azure, AI Foundry, Open-AI, Microsoft Copilot Studio, Machine Learning, Python, TensorFlow, PyTorch, scikit-learn, Large Language Models, LLM, Data preprocessing, REST API, Microservices architecture, MLOps, CI/CD for ML, Power-BI, Docker, Kubernetes, AI Ethics, Cloud Platforms, AWS, Google Cloud Platform, SQL, NoSQL, DevOps, Financial services, Regulatory environments Contract More ❯

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP More ❯

proven industry experience applying AI or machine learning (internship, placement, or full-time role) 🐍 Strong programming skills in Python and familiarity with frameworks such as TensorFlow , PyTorch , or scikit-learn 📊 Understanding of machine learning algorithms, data pipelines, and model evaluation ☁️ Familiarity with cloud platforms (AWS, GCP, or Azure) and version control tools (Git) 💬 Excellent communication, problem-solving, and More ❯

proven industry experience applying AI or machine learning (internship, placement, or full-time role) 🐍 Strong programming skills in Python and familiarity with frameworks such as TensorFlow , PyTorch , or scikit-learn 📊 Understanding of machine learning algorithms, data pipelines, and model evaluation ☁️ Familiarity with cloud platforms (AWS, GCP, or Azure) and version control tools (Git) 💬 Excellent communication, problem-solving, and More ❯

proven industry experience applying AI or machine learning (internship, placement, or full-time role) 🐍 Strong programming skills in Python and familiarity with frameworks such as TensorFlow , PyTorch , or scikit-learn 📊 Understanding of machine learning algorithms, data pipelines, and model evaluation ☁️ Familiarity with cloud platforms (AWS, GCP, or Azure) and version control tools (Git) 💬 Excellent communication, problem-solving, and More ❯

or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions More ❯

or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions More ❯

or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions More ❯

or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions More ❯

or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions More ❯

or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions More ❯

at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯